The aim of the meeting is to discuss recent developments, techniques and open questions in the area of abelian varieties and their moduli spaces, modular forms, number theory and combinatorics, automo...
La divulgazione scientifica contemporanea è spesso dominata da narrazioni che hanno poco a che fare con la pratica quotidiana della ricerca scientifica e privilegiano invece aspetti sensazionalistici ...
We study Fokker-Planck operators arising in the population density approach to networks of spiking neuron models, where a neuronal ensemble is described by a probability density evolving under drift–d...
The Rosenzweig-Porter (RP) model has recently gained a lot of attention as a paradigmatic (toy) model for studying localisation/delocalisation transitions.
In this talk, we report on a joint work wit...
The Space of Kahler potentials H (which has infinite dimension) can be thought as the limit of finite dimensional (!) symmetric spaces. This is known as Kähler quantization. In this talk we will take ...
A classical result due to Clebsch from the mid-nineteenth century confirms that every complex space sextic curve (given as an intersection of a quadric and a cubic surface in projective 3-space) has e...
Nonlocal energies, such as fractional Sobolev seminorms, arise naturally in mathematical models involving long-range interactions. In this talk, we study minimizers of such energies that vanish on a c...
There is an increasing interest in finding optimal conditions ensuring regularity of solutions to n-Laplacian type equations, so aims of this talk are
to give a complete picture of recent results of ...
This talk offers a gentle introduction to the theory of graph Laplacians. Wherever feasible, I will present results for undirected and directed graphs in parallel. After discussing classical results i...
Abstract: The Hopfield model represents a foundational paradigm in artificial intelligence, providing a prototypical example of an attractor neural network designed to implement associative memo...
The Hopfield model represents a foundational paradigm in artificial intelligence, providing a prototypical example of an attractor neural network designed to implement associative memory. Since its in...
